Evaluating near infrared spectroscopy for field prediction of soil properties
Budiman Minasny A C , Alex B. McBratney A , Leo Pichon A , Wei Sun A B and Michael G. Short AA Faculty of Agriculture, Food & Natural Resources, The University of Sydney, NSW 2006, Australia.
B China Agricultural University, East Campus, Research Center for Precision Agriculture, Qing Hua Dong Lu 17, Beijing, 100083, P.R. China.
C Corresponding author. Email: b.minasny@usyd.edu.au
Australian Journal of Soil Research 47(7) 664-673 https://doi.org/10.1071/SR09005
Submitted: 8 January 2009 Accepted: 24 July 2009 Published: 6 November 2009
Abstract
This paper demonstrates the application of near infrared diffuse reflectance spectroscopy (NIR-DRS) measurements as part of digital soil mapping. We also investigate whether calibration functions developed from a spectral library can be used for rapid characterisation of soil properties in the field. Soil samples were collected along 24 toposequences in the Pokolbin irrigation district, ~7 km2 of predominantly agricultural land in the Hunter Valley, NSW, Australia. Soil samples at 2 depths: 0–0.10 and 0.40–0.50 m were collected. The soil samples were scanned using NIR under 3 different conditions: field condition, dried unground, and dried ground. A separate spectral library containing soil laboratory measurements was used to develop functions to predict 3 main soil properties from NIR spectra (total C content, clay content, and sum of exchangeable cations). The absorbance spectra were found to be different for the 3 soil conditions. The field spectra appear to have higher absorbance, followed by dried unground samples and then dried ground samples. Although most spectral signatures or peaks were similar for the 3 soil conditions, field samples appear to have higher absorbance, particularly at 1400 nm and 1900 nm. The convex hull of the first 2 principal components of the soil spectra is an easy tool to evaluate the similarity of spectra from a calibration set to an observation. For field prediction, samples need to be calibrated using field samples. Finally, this study shows that NIR-DRS measurement is a useful part of digital soil mapping.
Additional keywords: diffuse reflectance infrared Fourier transform, soil organic carbon, infrared spectroscopy.
Acknowledgments
This work is supported by ARC Discovery project ‘High Resolution Digital Soil Mapping’. The authors wish to thank Drs Damien Field and Veronique Bellon for their valuable inputs, and 3 anonymous reviewers for their helpful comments.
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